1. Field of the Invention
The present invention relates to an X-ray image processing apparatus and method for performing image processing on radiographed X-ray images.
2. Description of the Related Art
Hitherto, an X-ray digital still image radiographing system using a flat panel detector (FPD) or a photo-stimulable phosphor determines an image processing parameter by analyzing a radiographed image. Then, image processing is performed using the image processing parameter. Thus, an optimal X-ray digital image for diagnosis is generated.
FIG. 10 illustrates a chest image that can be roughly segmented into a lung field region, a mediastinal region, and direct exposure regions outside a subject. Generally, the most important part for diagnosis of the chest image is the lung field region. The chest image whose lung field region has high contrast is required. The mediastinal region of the chest image does not need to have contrast as high as that of the lung field region. However, the chest image of the mediastinal region needs to have contrast which is not reduced to low levels and which can clearly be seen in detail. In order to obtain a chest image which satisfies such requirements, a segmentation process which analyzes an image and segments an entire image into a lung field region, a mediastinal region, and direct exposure regions is performed on the chest image.
One type of the segmentation process is a method using a histogram. When a histogram of the chest image illustrated in FIG. 10 is obtained, the histogram can be divided into three segments each having a peak which respectively correspond to the lung field region, the mediastinal region, and the direct exposure regions, as illustrated in FIG. 11A. Then, a range of pixel values (L1 through L2) corresponding to the mediastinal region, a range of pixel values (L2 through L3) corresponding to the lung field region, and a range of pixel values (L3 through L4) corresponding to the direct exposure regions can be obtained by extracting peaks and valleys in the histogram.
First, a binary image is created according to data in the range of pixel values (L1 through L2) corresponding to the mediastinal region of the chest image by performing a thresholding process in which as to pixels within the range of the pixel values (L1 through L2) of the mediastinal region of the chest image, a bit is “on”, and as to the pixels out of the range of the pixel values (L1 through L2), a bit is “off”. Further, in order to delete noise from the binary image, expansion/contraction processing which is general-purpose binary image processing is repeated. Consequently, a plurality of connected regions can be extracted. In addition, a region whose position and size are most appropriate to those of the mediastinal region can be selected from the plurality of connected regions by preliminarily obtaining statistics, such as average values and standard deviates of the position and the size of the mediastinal region in the chest image.
Similarly, the lung field region and the direct exposure regions can be determined, and the chest image can be segmented into the regions. Then, based on a result of region segmentation, which range the pixel values are included in can be determined with higher accuracy for each region. Thus, the range of pixel values (L1 through L2) corresponding to the mediastinal region, the range of pixel values (L2 through L3) corresponding to the lung field region, and the range of pixels values (L3 through L4) corresponding to the direct exposure regions are newly determined. Then, image processing is further performed on the basis of the newly determined ranges of pixel values of these regions, and a diagnostic image is obtained.
In order to obtain the diagnostic image, it is necessary to convert the contrast of the image. Thus, e.g., a pixel value conversion is performed in the image processing by performing gradation conversion using a lookup table. In the chest image, the range of pixel values (L1 through L4) of the entire image is expanded to a range of all pixel values, as illustrated in FIG. 11B. A pixel value conversion lookup table is generated so that the lung field region has a high gradient (high contrast), and a mediastinal region has a low gradient (low contrast). By performing the pixel value conversion using the lookup table, gradation of the chest image can be converted to have high contrast in the lung field without degrading the contrast of the mediastinal region. Further, in order to obtain detailed diagnostic information on the mediastinal region, low contrast is compensated by supplementing an image of the mediastinal region with high frequency components. How much the high frequency components are supplemented into the image of the mediastinal region is determined from the gradient in the pixel value of the mediastinal region in the lookup table.
Thus, a chest image suitable for image diagnosis of the chest is obtained by analyzing a radiographed image of the chest and performing image processing using information about the ranges of pixel values of the lung field region, the mediastinal region, and the direct exposure regions and information about the mediastinal region as image processing parameters.
Such image analysis is performed not only on a chest image. Various types of analysis may be performed on all sites, such as a skull region, a cervical vertebra region, a lumbar vertebra region, an abdominal region, a pelvis region, an articulation coxae region, and four limb regions, to obtain images more suitable for diagnosis. For example, Japanese Patent Application Laid-Open No. 11-151232 discusses extraction of a lung field region. Japanese Patent Application Laid-Open No. 2000-101840 discusses generation of a histogram, which is performed by deleting direct exposure regions. Japanese Patent Application Laid-Open No. 2000-163562 discusses extraction of a throat region.
Further, Japanese Patent Application Laid-Open No. 2002-282244 discusses extraction of a bone region. Japanese Patent Application Laid-Open No. 2002-330953 discusses deletion of a metal or radiation shielding material region. Japanese Patent Application Laid-Open No. 2003-16449 discusses techniques for performing analysis and image processing on an X-ray digital image to determine whether a direct exposure region is present.
Thus, algorithms for various types of analysis have been developed to improve the accuracy of the image. A dedicated analyzing program is used to analyze an image of each of the sites. The analyzing program is switched to the dedicated analyzing program corresponding to the radiographed site for every radiographing.
In a case of a still image radiographing system, site information about a site to be radiographed can be preliminarily obtained by the above techniques, e.g., an operator pushes a “site button” corresponding to the site to be radiographed before the site is radiographed. The site information is extremely important for analyzing a radiographed X-ray digital image. First, structure information indicating how many regions roughly constitute the radiographed image can be obtained from the site information. For example, a chest image can be roughly segmented into a lung field region, a mediastinal region, and direct exposure regions outside a subject. Therefore, it is extremely difficult to perform region segmentation processing without the site information. Further, if there is no information about a number of peaks to segment the histogram when peaks and valleys are extracted from a histogram, the system needs to segment the histogram by each of all possible numbers. Then, the system has to select a case where the degree of separation among regions respectively having peaks is highest. Thus, a huge amount of calculation is needed. In addition, results of calculation are low in precision and unstable.
Second, image processing method information indicating how an image is to be processed can be obtained from the site information. In the case of processing a chest image, it is necessary to set the contrast of the lung field region high and to obtain detail information about the mediastinal region. Thus, the pixel value conversion lookup table is generated from respective ranges of pixel values of the lung field region, the mediastinal region, and the direct exposure regions. Then, pixel value conversion by gradation conversion is performed using the lookup table. Subsequently, a process for supplementing the mediastinal region, which is obtained by the region segmentation process, with high frequency components in quantity determined according to a gradient in the pixel value of the mediastinal region in the lookup table is performed. Thus, if optimal image processing is performed on each of the sites, an image with an extremely high diagnostic value can be generated, as compared with an image which is uniformly processed without the site information.
However, a moving image radiographing system does not analyze an image using the site information. This is because a moving image of a subject is not radiographed by fixing a specific site of the subject. Since the moving image is radiographed while a radiographing direction and a radiographing position are continuously changed, site information corresponding only to the specific site is not enough to perform an analysis of the moving image, and continuous site information is needed therefor. Thus, an indefinitely large number of the site information is needed to analyze the moving image. However, it is impossible to use the indefinitely large number of site information. Accordingly, the moving image radiographing system does not perform high precision analysis and image processing using the site information.
One of main features of the moving image radiographing system is that X-ray exposure needs to be continuously controlled while a moving image is radiographed. The X-ray exposure can be controlled with good precision by an X-ray control parameter therefor which is obtained by utilizing results of high-precision analysis using the site information.
However, the high-precision analysis using the site information is not performed for the above-described reasons. Image processing and X-ray exposure control are performed by simplified methods. The simplified methods assume that a central portion of an image to be analyzed is a most-intended target site of observation. Upon this assumption, an area of interest is set in the central portion of the image. The image processing parameter and the X-ray control parameter are determined according only to information obtained in the area of interest. Then, image processing and X-ray exposure control are performed using these parameters.
For example, an average pixel value of the area of interest is calculated. Then, a pixel value conversion lookup table is created so that the average pixel value of the area of interest represents a constant luminance at all times. Subsequently, pixel value conversion using gradation conversion is performed.
Further, the average pixel value is used as an index value of an X-ray exposed dose of a patient who is a radiographed subject. X-ray radiographing conditions for an X-ray tube voltage and an X-ray tube current are controlled so that the average pixel value is to be a predetermined value.
However, according to the above-described moving image radiographing method, regardless of what subject is present at the central portion of an image, when a substance which is poor in X-ray permeability, e.g., an artificial bone is present at the central portion of the image, there are fears that necessary parts of the image may be unclearly displayed as a result of higher gradation conversion, and that excessive X-ray exposure may occur. That is, because the moving image radiographing system cannot use important site information, only poor precision and inaccurate image processing parameters and X-ray control parameters are obtained by the simplified methods. Accordingly, the conventional moving image radiographing method has a problem that a user thereof cannot obtain a desired radiographed image, i.e., a moving image effective for diagnosis.